class_docstr: Confusion Matrix for segmentation evaluation.
  
  Args:
      num_classes (int): Number of categories of the confusion matrix.
      streaming (bool): Whether to use streaming mode. If the value is set to True, the data will be
                        accumulated every time the `calculate` interface is called. Default to False.
docstr: Clear confusion matrix 
docstr_tok: ["Clear","confusion","matrix"]
code: def zero_matrix(self):
      """Clear confusion matrix"""
      self.confusion_matrix = np.zeros(
          [self.num_classes, self.num_classes], dtype="int64"
      )
  
imports: import os
  from typing import Callable, Union, List, Tuple
  import cv2
  import paddle
  import PIL
  import numpy
  import paddle.nn.functional
  from scipy.sparse import csr_matrix
label_desc: Use image node_id 3 for calling the ConfusionMatrix obj's underlying member method code with example usage: obj.zero_matrix() without return types